---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.82
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hubert-base-ls960-finetuned-gtzan

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5845
- Accuracy: 0.82

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0942        | 0.99  | 89   | 2.0216          | 0.33     |
| 1.713         | 1.99  | 179  | 1.5801          | 0.43     |
| 1.3519        | 2.99  | 269  | 1.2871          | 0.62     |
| 1.182         | 3.99  | 359  | 1.1647          | 0.65     |
| 1.0645        | 4.99  | 449  | 0.9332          | 0.71     |
| 0.8777        | 6.0   | 539  | 0.8251          | 0.77     |
| 0.7           | 7.0   | 629  | 0.8725          | 0.77     |
| 0.4387        | 8.0   | 719  | 0.8215          | 0.77     |
| 0.567         | 9.0   | 809  | 0.5571          | 0.85     |
| 0.5342        | 9.9   | 890  | 0.5845          | 0.82     |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.13.1
- Datasets 2.13.1
- Tokenizers 0.13.3